Agile replacement with agent workflows
PFF cuts scrum entirely, hits 10x feature output with two engineers running agent workflows AI EngineerTL;DW
- PFF's 2-engineer agentic team deployed 25x more frequently than 10-engineer traditional team, with 10x higher output when blending ticket count and code complexity metrics.
- Customer satisfaction improved from 7/7.5 to 8.6/10 after replacing Scrum with agentic workflows, directly validating quality gains.
- Eliminated sprint planning, daily standups, and sprint refinement by automating spec→lightweight design document→ticket→PR generation via agents.
- Used half-hour huddles every other day with engineers, product, and design instead of multiple Scrum ceremonies; deployed to production in MVP state for fast feedback.
- Agent-driven QA automatically tests against acceptance criteria post-deployment to staging; future: agents will auto-create PRs to fix failures.
- Offload opinionated code reviews (variable names, style) to agents; keep humans for system design, product feel, and security decisions.
- Started with strongest engineers in non-critical systems before scaling; slow phased rollout beats enterprise-wide simultaneous onboarding.
- Encode engineering culture and patterns as reusable composable skills (e.g., feature flags, service-repository pattern, API design) to prevent drift.
- Aim for deterministic, verifiable tasks with clear acceptance criteria in lightweight design documents to prevent overengineering by agents.
- Begin with boring, repetitive tasks engineers hate; question every existing process for actual value before keeping it.
TL;DW
- PFF's 2-engineer agentic team deployed 25x more frequently than 10-engineer traditional team, with 10x higher output when blending ticket count and code complexity metrics.
- Customer satisfaction improved from 7/7.5 to 8.6/10 after replacing Scrum with agentic workflows, directly validating quality gains.
- Eliminated sprint planning, daily standups, and sprint refinement by automating spec→lightweight design document→ticket→PR generation via agents.
- Used half-hour huddles every other day with engineers, product, and design instead of multiple Scrum ceremonies; deployed to production in MVP state for fast feedback.
- Agent-driven QA automatically tests against acceptance criteria post-deployment to staging; future: agents will auto-create PRs to fix failures.
- Offload opinionated code reviews (variable names, style) to agents; keep humans for system design, product feel, and security decisions.
- Started with strongest engineers in non-critical systems before scaling; slow phased rollout beats enterprise-wide simultaneous onboarding.
- Encode engineering culture and patterns as reusable composable skills (e.g., feature flags, service-repository pattern, API design) to prevent drift.
- Aim for deterministic, verifiable tasks with clear acceptance criteria in lightweight design documents to prevent overengineering by agents.
- Begin with boring, repetitive tasks engineers hate; question every existing process for actual value before keeping it.
A three-month case study at sports-data firm PFF found two senior engineers using Claude for spec generation, ticket creation, code review, and autonomous QA outperformed a 10-person scrum team—25x more deploys, 10x weighted feature output, customer satisfaction up from 7.5 to 8.6. Stand-ups, sprint planning, and PMs were eliminated.